中心型时间地图的构建方法与实现

王丽娜; 李响; 江南; 杨振凯; 杨飞

doi:10.11947/j.AGCS.2018.20170180

测绘学报 >

2018 , Vol. 47 >Issue 1: 123 - 132

DOI: https://doi.org/10.11947/j.AGCS.2018.20170180

地图学与地理信息

中心型时间地图的构建方法与实现

王丽娜 ,
李响 ,
江南 ,
杨振凯 ,
杨飞

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信息工程大学地理空间信息学院, 河南郑州 450052

王丽娜(1987-),女,博士生,主要研究方向为地理信息可视化。E-mail:wln_map@126.com

收稿日期: 2017-02-23

修回日期: 2017-10-23

网络出版日期: 2018-02-05

基金资助

国家自然科学基金青年科学基金（41401467）；国家重点研发计划项目（2016YFB0502300）

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A New Method of Constructing a Central Time-space Map

WANG Lina ,
LI Xiang ,
JIANG Nan ,
YANG Zhenkai ,
YANG Fei

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Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450052, China

Received date: 2017-02-23

Revised date: 2017-10-23

Online published: 2018-02-05

Supported by

The National Natural Science Foundation of China(No. 41401467);National Key Research and Development Program(No. 2016YFB0502300)

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摘要

中心型时间地图是表达各个点到中心点时间距离的一种有效可视化方法。本文提出一种基于移动最小二乘法的中心型时间地图的构建方法。与以往的研究方法相比，该方法解决了中心型时间地图构建中出现的3个问题：①通过距离恒定性等原则解决了时间地图与原地图的尺度一致性问题；②通过约束条件的控制解决了转换过程中出现的拓扑错误问题；③通过多种可视化方法解决了时间地图变形的可视化表达问题。最后，以2016年度北京市到全国307个市县的真实铁路时间数据为例，构建了以北京市为中心的时间地图，该时间地图以全新的视角展示了北京市与全国各城市间的时间距离关系，并为进一步揭示和挖掘中国铁路交通发展状况的规律和趋势提供了可视化依据。

关键词： 时间距离可视化; 时间地图; 移动最小二乘法; 空间变形

本文引用格式

王丽娜 , 李响 , 江南 , 杨振凯 , 杨飞 . 中心型时间地图的构建方法与实现[J]. 测绘学报, 2018 , 47(1) : 123 -132 . DOI: 10.11947/j.AGCS.2018.20170180

Abstract

A central time-space map is an effective method for representing time distance from any positions to a given point on a map.We proposed a new method of generating a central time-space map based on moving least squares(MLS).Compared with other methods,our method solved the following 3 problems:①the law of consistency of distance was used to keep the same scale of a time-space map and its original map;②we used some constraints to adjust topological errors generated by the process of transformation;③many visualization methods were used to represent a time-space map's distortion.Finally,we took real trains' timetable data in China in 2016 as a case study to generate a time-space map with Beijing as the center.The results showed that the time distance relationship between Beijing and other cities from a different perspective and were also helpful for further discovering some knowledge and trends of the development of railway transportation in China.

Key words： time-distance visualization; time-space map; moving least squares(MLS); spatial distortion

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